Even if this works as intended, the hardware is needs at least another order of magnitude precision to be able to use gradient descent methods. Without that you're stuck with genetic or other less effective strategies to train models.

I also have concerns that this is quite unlikely to be able to have sufficiently uncorrelated randomness in all channels to be useful in practical applications.